Publications

Book

Das, S. Artificial Intelligence in Highway Safety. CRC Press, Boca Raton, FL. 2022.

Artificial Intelligence in Highway Safety provides cutting-edge advances in highway safety using AI. The author is a highway safety expert. He pursues highway safety within its contexts, while drawing attention to the predictive powers of the AI techniques in solving complex problems for safety improvement. This book provides both theoretical and practical aspects of highway safety. Each chapter contains theory and its contexts in plain language with several real-world examples.

Publisher: CRC Press. Publication Date: September 29, 2022.

 

Peer Reviewed Journal Articles

2022

  1. Wei, Z.*, S. Das, and Y. Zhang. Short Duration Crash Prediction for Rural Two-lane Roadways: Applying Explainable Artificial Intelligence. Transportation Research Record (in press).     TRR
  2. Das, S., M. Le, K. Fitzpatrick, and D. Wu. Did Operating Speeds During COVID-19 Result in More Fatal and Injury Crashes on Urban Freeways? Transportation Research Record (in press).     TRR
  3. Obaid, I., Alnedawi, A., Aboud, G. M., Tamakloe, R., Zuabidi, H., and Das, S. Factors associated with driver injury severity of motor vehicle crashes on sealed and unsealed pavements: random parameter model with heterogeneity in means and variances. International journal of transportation science and technology.     IJTST
  4. Das, S., M. Hossain, M. Rahman, X. Kong, X. Sun, and G. Mamun. Understanding patterns of moped and seated motor scooter (50 cc or less) involved fatal crashes using cluster correspondence analysis. Transportmetrica A: Transport Science.     TA
  5. Kong, X., A, Zhang, X, Xiao, S, Das , and Y. Zhang. Work from home in the post-COVID world. Case Studies on Transport Policy.     CSTP
  6. Rahman, A., X. Sun, and S. Das , and Y. Zhang. Using Cluster Correspondence Analysis to Explore Rainy Weather Crashes in Louisiana. Transportation Research Record: Journal of the Transportation Research Board     TRR
  7. Tamakloe, R., Sam, E. F., Bencekri, M., Das, S., and Park, D. Mining groups of factors influencing bus/minibus crash severities on poor pavement condition roads considering different lighting status. Traffic injury prevention.     TIP
  8. Hossain, M. M., Zhou, H., Das, S., Sun, X., and Hossain, A. Young drivers and cellphone distraction: Pattern recognition from fatal crashes. Journal of Transportation Safety & Security.     JTSS
  9. Kong, X., Li, Z., Zhang, Y., and Das, S. Bridge Deck Deterioration: Reasons and Patterns. Transportation Research Record: Journal of the Transportation Research Board.     TRR
  10. Khodadadi, A.*, D. Lord, I. Tsapakis, A. Shirazi, and S. Das. Derivation of the Empirical Bayesian method for the Negative Binomial-Lindley generalized linear model: Application in various safety analyses. Accident Analysis & Prevention. Vol. 170.     AAP
  11. Tamakloe, R., Park, D., and S. Das. Factors affecting motorcycle crash casualty severity at signalized and non-signalized intersections in Ghana: insights from a data mining and binary logit regression approach. Accident Analysis & Prevention. Vol. 165.     AAP
  12. Kutela, B., S. Das, and B. Dadashova. Mining patterns of autonomous vehicle crashes involving vulnerable road users to understand the associated factors. Accident Analysis & Prevention. Vol. 165.     AAP
  13. Tsapakis, I., Das, S., S. Jessberger, W. Holik, and P. Anderson. Improving Stratification Procedures to Estimate Annual Average Daily Traffic (AADT) for Non-Federal Aid-System (NFAS) Roads. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2676, Iss. 2, pp. 393-406.     TRR
  14. Das, S., and Dutta, A. Twelve Years of Transportation Annual Meeting Hashtag: Implications for Networking and Research Trends. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2675, Iss. 1, pp. 763-772.     TRR
  15. Das, S., X. Sun, B. Dadashova, M. Rahman, and M. Sun. Sun Glare and Traffic Crashes: Identifying Patterns of Key Factors. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2676, Iss. 2, pp. 165-175.     TRR
  16. Fitzpatrick, K., A. Do, S. Das, R. Avelar, and M. Pratt. Improving Pedestrian Safety at Signalized Intersections: Impacts of Corner Radius. ITE Journal. ITE
  17. Kong, X., S. Das, Zhang, Y., Wu, L., and Wallis, J. In-Depth Understanding of Near-Crash Events Through Pattern Recognition. Transportation Research Record. TRR
  18. Hasan, A., Jalayer, M., and S. Das. Severity Modeling of Work Zone Crashes in New Jersey Using Machine Learning Models. Journal of Transportation Safety and Security. JTSS
  19. Das, S., Sarkar, S., and Park, E. Impact of Operating Speed Measures on Traffic Crashes: Annual and Daily Level Models for Rural Two-lane and Rural Multilane Roadways. Journal of Transportation Safety and Security. JTSS
  20. Das, S., Aman, J., and Sarkar, S. News media mining to explore speed-crash-traffic association during COVID-19. Transportation Research Record TRR
  21. Das, S., Aman, J. and Rahman, A. Content Analysis on Homelessness Issues at Airports by News Media Mining. Transportation Research Record TRR
  22. Hossain, M., Zhou, H., Rahman, M., Das, S., and Sun, X. Cellphone-Distracted Crashes of Novice Teen Drivers: Understanding Associations of Contributing Factors for Crash Severity Levels and Cellphone Usage Types. Traffic Injury Prevention. TIP

2021

  1. Das, S., R. Tamakloe, H. Zubaidi, I. Obaid, and A. Alnedawi. Fatal pedestrian crashes at intersections: Trend mining using association rules. Accident Analysis & Prevention. Vol. 160.     AAP
  2. Kong, X. *, Das, S., H. Zhou, and Y. Zhang. Patterns of near-crash events in a naturalistic driving dataset: applying rules mining. Accident Analysis & Prevention. Vol. 161.     AAP
  3. Das, S., A. Dutta, and M. Rahman. Pattern recognition from light delivery vehicle crash characteristics. Journal of Transportation Safety & Security.     JTSS
  4. Das, S., K. Dey, and M. Rahman. Pattern Recognition from Cyclist Under Influence (CUI) Crash Events. Journal of Substance Use.     JSU
  5. Kong, X. *, Das, S., and Y. Zhang. Mining patterns of near-crash events with and without secondary tasks. Accident Analysis & Prevention. Vol. 157.     AAP
  6. Das, S.. Autonomous Vehicle Safety: Understanding Perceptions of Pedestrians and Bicyclists. Transportation Research Part F: Traffic Psychology and Behaviour. Vol. 81, pp. 41-54.     TR-F
  7. Das, S., Z. Wei*, X. Kong*, and X. Xiao*. Mining crowdsourced data on bicycle safety critical events. Transportation Research Interdisciplinary Perspectives. Vol. 10.     TRIP
  8. Zubaidi, H.*, I. Obaid,*, A. Alnedawi, Das, S., and MM Haque. Temporal instability assessment of injury severities of motor vehicle drivers at give-way controlled unsignalized intersections: A random parameters approach with heterogeneity in means and variances. Accident Analysis & Prevention. Vol. 156.     AAP
  9. Kong, X. *,Das, S., H. Zhou, and Y. Zhang. Lessons learned from pedestrian-driver communication and yielding patterns. Transportation Research Part F: Traffic Psychology and Behaviour. Vol. 79, pp. 35-48.     TR-F
  10. Khodadadi, A. *, I. Tsapakis,Das, S., and D. Lord. Application of Different Negative Binomial Parameterizations to Develop Safety Performance Function for Non-Federal Aid System Roads. Accident Analysis & Prevention. Vol. 156.     AAP
  11. Rahman, M. K. Dey, Das, S., and M. Sherfinski. Sharing the Road with Autonomous Vehicles: A Qualitative Analysis of the Perceptions of Pedestrians and Bicyclists. Transportation Research Part F: Traffic Psychology and Behaviour. Vol. 78, pp. 433-445.     TR-F
  12. Das, S., and H. Zubaidi*. City Transit Rider Tweets: Understanding Sentiments and Politeness. Journal of Urban Technology.     JUT
  13. Park, E., K. Fitzpatrick, Das, S., and R. Avelar. Exploration of the relationship among roadway characteristics, operating speed, and crashes for city streets using path analysis. Accident Analysis & Prevention. Vol. 150.     APP
  14. Zubaidi, H.*, I. Obaid, I.*, A. Alnedawi, and Das, S. Motor Vehicle Driver Injury Severity Analysis Utilizing A Random Parameter Binary Probit Model Considering Different Types of Driving Licenses in 4-Legs Roundabouts in South Australia. Safety Science. Vol. 134.     SS
  15. Das, S., and H. Zubaidi*. Last Forty Years of ITE Journal Articles: A Scientometric Overview. ITE Journal Online Exclusive.     ITE
  16. Das, S., S. Datta*, H. Zubaidi*, and I. Obaid*. Applying interpretable machine learning to classify tree and utility pole related crash injury types. IATSS Research. Vol. 45, Iss. 3, pp. 310-316.     IATSS
  17. Das, S., Mousavi, M.*, and Shirinzad, M*. Speeding Related Motorcycle Injuries: Findings from Cluster Correspondence Analysis. Journal of Traffic Safety and Security.     JTSS
  18. Das, S., X. Kong*, S. Lavrenz, M. Jalayer, and L. Wu. Pattern Recognition from Rail Grade Crossing Fatal Crashes. International Journal of Transportation Science and Technology. Vol. 11, Iss. 1, pp. 107-117.     IJTST
  19. Rahman, M., X. Sun, Das, S., and S. Khanal. Exploring the Influential Factors of Roadway Departure Crashes on Rural Two-Lane Highways with Logit Model and Association Rules Mining. International Journal of Transportation Science and Technology. Vol. 10, Iss. 2, pp. 167-183.     IJTST
  20. Das, S., I. Tsapakis, and A. Khodadadi*. Safety Performance Functions for Low-Volume Rural Minor Collector Two-lane Roadways. IATSS Research. Vol. 45, Iss. 3, pp. 347-356.     IATSS
  21. Das, S. An Exploratory Analysis of Unmanned Aircraft Sightings using Text Mining. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2675, Iss. 5, pp. 291-300.     TRR
  22. Das, S., Dutta, A., and Tsapakis, I. Motorcycle Crash Causation Study: Exploratory Topic Models from Crash Narrative Reports. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2675, Iss. 9, pp. 449-462.     TRR
  23. Das, S., and Dutta, A. Light Delivery Vehicles Crashes: Identifying Insights using Joint Dimension Reduction and Clustering. Transportation Research Record: Journal of the Transportation Research Board.     TRR
  24. Das, S. Fatal Crash Reporting in Media: A Case Study on Bangladesh. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2675, Iss. 10, pp. 960-971.     TRR
  25. Fitzpatrick, K., Das, S., T. Gates, K. Dixon, and E. Park. Considering Roadway Context in Setting Posted Speed Limits. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2675, Iss. 8, pp. 590-602.     TRR
  26. Das, S., and A. Dutta. Characterizing Public Emotions and Sentiments in COVID-19 Environment: A Case Study of India. Journal of Human Behavior in the Social Environment. Vol. 31, Iss. 1-4, pp. 154-167.     jhbse
  27. Das, S. Data Dive into Transportation Research Record Articles: Authors, Coauthorships, and Research Trends. TR News. Iss. 331, pp. 25-31.     TRN

2020

  1. Jalayer, M., M. Pour-Rouholamin, D. Patel, Das, S., and H. Parvardeh, H. A Penalized-likelihood Approach to Characterizing Bridge related Crashes in New Jersey. Traffic Injury Prevention. Vol. 22, Iss. 1, pp. 63-67.     TIP
  2. Das, S. Traffic Volume Prediction in Low-Volume Roadways: Cubist Approach. Transportation Planning and Technology. Vol. 44, Iss. 1, pp. 93-110.     TPT
  3. Das, S., X.Sun, and M. Sun. Rule-based safety prediction models for rural two-lane run-off-road crashes. International Journal of Transportation Science and Technology. Vol. 10, Iss. 3, pp. 235-244.     IJTST
  4. Das, S., Dutta, A., Dey, K., Jalayer, M., and Mudgal, A. Vehicle involvements in hydroplaning crashes: Applying interpretable machine learning. Transportation Research Interdisciplinary Perspectives. Vol. 6.     TRIP
  5. Kong, X., Das, S., K. Jha, and Y. Zhang. Understanding Speeding Behavior from Naturalistic Driving Data: Applying Classification Based Association Mining. Accident Analysis and Prevention. Vol. 144.     AAP
  6. Das, S., A. Dutta, and K. Fitzpatrick. Technological Perception on Autonomous Vehicles: Perspectives of the Non-motorists. Technology Analysis & Strategic Management. Vol. 32, Iss. 11, pp. 1335-1352.     TASM
  7. Das, S. Identifying key patterns in motorcycle crashes: findings from taxicab correspondence analysis. Transportmetrica A: Transport Science. Vol. 17, Iss. 4, pp. 593-614.     TA
  8. Das, S., M. Le, and B. Dai. Application of Machine Learning Tools in Classifying Pedestrian Crash Types: A Case Study. Transportation Safety and Environment. Vol. 2, Iss. 2, pp. 106-119.     TSE
  9. Das, S., S. Geedipally, and K. Fitzpatrick. Inclusion of Speed and Weather Measures in Safety Performance Functions for Rural Roadways. IATSS Research. Vol. 45, Iss. 1, pp. 60-69.     IATSS
  10. Das, S., S. Ashraf*, L. Tran*, and A. Dutta. Pedestrians Under Influence (PUI) Crashes: Patterns from Correspondence Regression Analysis. Journal of Safety Research. Vol. 75, pp. 14-23.     JOSR
  11. Das, S., L. Tran*, and M. Theel*. Understanding Patterns in Marijuana Impaired Traffic Crashes: A Case Study. Journal of Substance Use. Vol. 26, Iss. 1, pp. 21-29.     JSU
  12. Das, S., and S. Geedipally. Rural Speed Safety Project for USDOT Safety Data Initiative: Findings and Outcomes. ITE Journal. September Issue. Vol. 9, Iss. 9, pp. 38-44.     ITE
  13. Das, S., and A. Dutta. Extremely serious crashes on urban roadway networks: Patterns and trends. IATSS Research. Vol. 44, Iss. 3, pp. 248-252.     IATSS
  14. Das, S., X. Sun, S. Goel*, M. Sun, A. Rahman, and A. Dutta. Flooding related Traffic Crashes: Findings from Association Rules. Journal of Transportation Safety and Security. Vol. 14, Iss. 1, pp. 111-129.     JTSS
  15. Das, S., and L. White. RuralSpeedSafetyX: Interactive Decision Support Tool to Improve Safety. SoftwareX. Vol. 11.     SoftwareX
  16. Rahman, M., X. Sun, and Das, S. Reconfiguring Urban Undivided Four-Lane Highways to Five-Lane: An Unideal but Very Effective Solution for Crash Reduction. ASCE Journal of Transportation Engineering, Part A: Systems. Vol. 146, Iss. 10.     JTEA
  17. Das, S., and G. Griffin. Investigating the Role of Big Data in Transportation Safety. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2674, Iss. 6, pp. 244-252.     TRR
  18. Das, S., Dutta, A., Tsapakis, I. Automated vehicle collisions in California: Applying Bayesian latent class model. IATSS Research. Vol. 44, Iss. 4, pp. 300-308.     IATSS
  19. Das, S., Dutta, A., and Brewer, M. Transportation Research Record Articles: A Case Study of Trend Mining. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2674, Iss. 10, pp. 1-14.     TRR
  20. Das, S., Islam, M., Dutta, A., and Shimu, T*. Uncovering Deep Structure of Determinants in Large Truck Fatal Crashes. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2674, Iss. 9, pp. 742-754.     TRR
  21. Geedipally, S., Das, S., Pratt, M., and Lord D. Determining Skid Resistance Needs on Horizontal Curves for Different Levels of Precipitation. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2674, Iss. 9, pp. 358-370.     TRR
  22. Dadashova, B., G. Griffin, Das, S., S. Turner, and B. Sherman. Estimation of Average Annual Daily Bicycle Counts using Crowdsourced Strava Data. Transportation Research Record: Journal of the Transportation Research Board. (in press).     TRR
  23. Das, S., and I. Tsapakis. Interpretable Machine Learning Approach in Estimating Traffic Volume on Low-Volume Roadways. International Journal of Transportation Science and Technology. Vol 9, Iss. 1, pp. 76-88.     IJTST

2019

  1. Das, S.. #TRBAM: Social Media Interactions from Transportation’s Largest Conference TR News, Iss. 324, pp 18-23.     JHBSE
  2. Trueblood, A. B., Pant, A., Kim, J., Kum, H. C., Perez, M., Das, S., & Shipp, E. A semi-automated tool for identifying agricultural roadway crashes in crash narratives. Traffic Injury Prevention, Vol. 20(4), pp. 413-418.     TIP
  3. Fitzpatrick, K, McCourt, R., and Das, S. Current Attitudes among Transportation Professionals with Respect to the Setting of Posted Speed Limits. Transportation Research Record: Journal of the Transportation Research Board, Vol. 2673, Iss. 4, pp. 778-788.     TIP
  4. Das, S., and A. Bibeka*. Understanding Crime and Demographic Influence on Non-motorized Trips: Macro-level Analysis. Journal of Human Behavior in the Social Environment. Vol 30, Iss. 3, pp. 251-264.     JHBSE
  5. Das, S., B. Storey, T. Shimu*, S. Mitra, M. Theel*, and B. Maraghepour*. Severity Analysis of Tree and Utility Pole Crashes: Applying Fast and Frugal Heuristics. IATSS Research. Vol 44, Iss. 2, pp. 85-93.     IATSS
  6. Das, S., A. Dutta, and S. Geedipally. Applying Bayesian Data Mining to measure the Effect of Vehicular Defects on Crash Severity. Journal of Transportation Safety & Security. Vol 13, Iss. 6, pp. 605-621.     JTSS
  7. Das, S., L. Kyle, L. Wu, and R. Henk. Understanding Crash Potential Associated with Teen Driving: Survey Analysis using Multivariate Graphical Method. Journal of Safety Research. Vol 70, pp. 213-222.     JOSR
  8. Das, S., X. Kong*, and I. Tsapakis. Hit and Run Crash Analysis using Association Rules Mining. Journal of Transportation Safety and Security. Vol 13, Iss. 2, pp. 123-142.     JTSS
  9. McCourt, R., K. Fitzpatrick, P. Koonce, and Das, S. Speed Limits: Leading to Change. ITE Journal, pp. 40-45.     ITE
  10. Jalayer, M., and S. Das. Application of Unmanned Aerial vehicle to Inspect and Inventory Interchange Assets to Mitigate Wrong-Way Entries. ITE Journal. Vol 89, Iss. 7, pp. 37-42.     ITE
  11. Das, S., A. Dutta, and X. Sun. Patterns of Rainy Weather Crashes: Applying Rules Mining. Journal of Transportation Safety and Security. Vol 12, Iss. 9, pp. 1083-1105.     JTSS
  12. Das, S., M. Le, M. Pratt, and C. Morgan. Safety effectiveness of truck lane restrictions: a case study on Texas urban corridors. International Journal of Urban Sciences. Vol 24, Iss. 1, pp. 35-49.     IJUS
  13. Das, S., I. Tsapakis, and S. Datta*. Safety Performance Functions of Low-Volume Roadways. Transportation Research Record: Journal of the Transportation Research Board. Vol 2673, Iss. 12, pp. 798-810.     TRR
  14. Das, S., K. Jha, K. Fitzpatrick, M. Brewer, and T. Shimu*. Pattern Identification from Elderly Cyclist Fatal Crashes. Transportation Research Record: Journal of the Transportation Research Board. Vol 2673, Iss. 6, pp. 638-649.     TRR
  15. Das, S., A. Dutta, T. Lindheimer, M. Jalayer, and Z Elgart. YouTube as a Source of Information in Understanding Autonomous Vehicle Consumers: A Natural Language Processing (NLP) Study. Transportation Research Record: Journal of the Transportation Research Board. Vol 2673, Iss. 8, pp. 242-253.     TRR
  16. Das, S., A. Bibeka*, X. Sun, T. Zhou, and M. Jalayer. Elderly Pedestrian Fatal Crash Related Contributing Factors: Applying Empirical Bayes Geometric Mean Method. Transportation Research Record: Journal of the Transportation Research Board. Vol 2673, Iss. 8, pp. 254-263.     TRR
  17. Das, S., S. Geedipally, K. Dixon, X. Sun, and C. Ma*. Measuring the Effectiveness of Vehicle Inspection Regulations in Different States of the U.S. Transportation Research Record: Journal of the Transportation Research Board. Vol 2673, Iss. 5, pp. 208-219.     TRR

2018

  1. Das, S., A. Dutta, R. Avelar, K. Dixon, X. Sun, and M. Jalayer. Supervised Association Rules Mining on Pedestrian Crashes in Urban Areas: Identifying Patterns for Appropriate Countermeasures. International Journal of Urban Sciences. Vol 23, Iss. 1, pp. 30-48.     IJUS
  2. Das, S., A. Dutta, Kong, X. *, and Sun, X. Hit and Run Crashes: Knowledge Extraction from Bicycle Involved Crashes using First and Frugal Tree. International Journal of Transportation Science and Technology. Vol 8, Iss. 2, pp. 146-160.     IJTST
  3. Das, S., A. Dutta, G. Medina, L. Minjares-Kyle, and Z. Elgart. Extracting patterns from Twitter to promote biking. Vol 43, Iss. 1, pp. 51-59.     IATSS
  4. Das, S., A. Dutta, M. Jalayer, A. Bibeka*, and L. Wu. Factors influencing the patterns of wrong-way driving crashes on freeway exit ramps and median crossovers: exploration using ‘Eclat’ association rules to promote safety. International Journal of Transportation Science and Technology, Vol. 7 Iss. 2, pp. 114-123.     IJTST
  5. Das, S., R. Avelar, K. Dixon, and X. Sun. Investigation on the Wrong Way Driving Crash Patterns using Multiple Correspondence Analysis. Accident Analysis and Prevention. Vol. 111, pp. 43-55.     AAP
  6. Das, S., A. Dutta, K. Dixon, L. Minjares-Kyle, and G. Gillette. Using Deep Learning in Severity Analysis of At-Fault Motorcycle Rider Crashes. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2672, Iss. 34, pp. 122-134.     TRR
  7. Das, S., A. Mudgal, A. Dutta, and S. Geedipally. Vehicle Consumer Complaint Reports Involving Severe Incidents: Mining Large Contingency Tables. Transportation Research Record: Journal of the Transportation Research Board. Vol. 2672, Iss. 32, pp. 77-82.     TRR
  8. Das, S., X. Sun, K. Dixon, and A. Rahman. Safety Effectiveness of Roadway Conversion with a Two Way Left Turn Lane. Journal of Traffic and Transportation Engineering. Vol. 5, Iss. 5, pp. 309-317.     JTTE

2017

  1. Das, S., B. Brimley, T. Lindheimer, and M. Zupancich*. Association of Reduced Visibility with Crash Outcomes. IATSS Research. Vol. 42, Iss. 3, pp. 143-151.     IATSS
  2. Das, S., K. Dixon, X. Sun, A. Dutta, and M. Zupancich*. Trends in Transportation Research: Exploring Content Analysis in Topics. Transportation Research Record: Journal of the Transportation Research Board, Vol. 2614, pp. 27–38.     TRR

2016

  1. Das, S., X. Sun, and A. Dutta. Text Mining and Topic Modeling on Compendium Papers from Transportation Research Board Annual Meetings. Transportation Research Record: Journal of the Transportation Research Board, Vol. 2552, pp. 48-56.     TRR
  2. Das, S., and X. Sun. Association knowledge for fatal run-off-road crashes by Multiple Correspondence Analysis. IATSS Research, Vol. 39, Iss. 2, pp. 146–155.     IATSS

2015

  1. Das, S., and X. Sun. Factor Association with Multiple Correspondence Analysis in Vehicle-Pedestrian Crashes. Transportation Research Record: Journal of the Transportation Research Board, Vol. 2519, Iss. 1, pp. 95-103.     TRR
  2. Das, S., X. Sun, F. Wang, and C. Leboeuf. Estimating likelihood of future crashes for crash-prone drivers. Journal of Traffic and Transportation Engineering, Vol. 2, Iss. 3, pp. 145-157.     JTTE
  3. Khattak, M., A. Khattab, H. Rizvi, S. Das, and M. Bhuyan. Imaged-based Discrete Element Modeling of Hot Mix Asphalt Mixtures. Materials and Structures, Vol. 48, Iss. 8, pp. 2417–2430.     MS
  4. Das, S., X. Sun, and A. Dutta. Investigating User Ridership Sentiments for Bike Sharing Programs. Journal of Transportation Technologies, Vol. 5, Iss.2, pp. 69-75.     JTT

2014

  1. Sun, X., S. Das, Z. Zhang, F. Wang, and C. Leboeuf. Investigating Safety Impact of Edgelines on Narrow, Rural Two-Lane Highways by Empirical Bayes Method. Transportation Research Record: Journal of the Transportation Research Board, Vol. 2433, pp. 121-128.     TRR
  2. Sun, X., S. Das, and Y. He. Analyzing Crash-Prone Drivers in Multiple Crashes for Better Safety Educational and Enforcement Strategies. Journal of Transportation Technologies, Vol. 4, Iss.1, pp. 93-100.     JTT

2013

  1. Das, S., X. Sun, Y. He, F. Wang, and C. Leboeuf. Investigating the Safety Impact of Raised Pavement Markers on Freeways in Louisiana. International Journal of Engineering Research & Innovation, Vol. 5, Iss. 2, pp. 74-80.     IJERI
  2. Sun, X., S. Das, N. Fruge, R. Bertinot, and D. Magri. Four-Lane to Five-Lane Urban Roadway Conversions for Safety. Journal of Transportation Safety & Security, Vol. 5, Iss. 2, pp. 106-117.     JTSS

Book Chapters

Das, S., S. Chatterjee, and S. Mitra. Improper Passing and Lane-Change related Crashes: Pattern Recognition using Association Rules Negative Binomial Mining. Computational Methods and Data Engineering. Springer. 2021.

The chapter written by Das et al. used Florida rural roadway crash data from the second Strategic Highway Research Program (SHRP2) to investigate improper passing/lane-change related crashes. This study applied an unsupervised data mining technique (known as association rules negative binomial (NB) miner) to extract the knowledge pattern of co-occurrence of the significant variables.

Publisher: Springer. Year: 2021.

 

Das, S. Impact of COVID-19 on industries. COVID-19 and the Environment Impact, Concerns & Management, Elsevier. 2021.

Utilizing case studies, this book presents examples of various issues around handling these impacts, as well as policies and strategies being developed as a result. Subasish wrote a chapter on the impact of COVID-19 on different industries. This study performed a robust before-after analysis by collecting historical employment data from the U.S. Bureau of Statistics. The findings of the study will be beneficial in under- standing the temporal influence of this pandemic on several industrial sectors in the US.

Publisher: Elsevier. Year: 2021.

 

Dutta, A., and S. Das. Tweets about Self Driving Cars: Deep Sentiment Analysis using Long Short-Term Memory network (LSTM). International Conference on Innovative Computing and Communications. Springer. 2021.

This book chapter presents an empirical investigation of consumer sentiment toward self-driving cars or autonomous vehicles (AVs) based on the acquired self-driving car-related tweets. Information retrieval in social media is a complex task that requires technical insights. This study used a hierarchical attention-based long short-term memory network (LSTM), a popular deep learning tool.

Publisher: Springer. Year: 2021.

 

Das, S. Non-fear-based Road Safety Campaign as a Community Service: Contexts from Social Media. Communication in Computer and Information Science. Springer. 2020.

Non-fear-based safety campaigns are limited in number, and their impact is significant in changing public attitudes towards safety. This study collected YouTube comment data from two non-fear-based safety campaigns and compared their impacts by using natural language processing tools.

Publisher: Springer. Year: 2020.

 

Das, S. Automobile Safety Inspection. International Encyclopedia of Transportation, Elsevier. Amsterdam, Netherlands.

Earlier studies do not implicate that safety inspection programs have zero effect on the reduction of crashes; however, the results are inconclusive. Additionally, international studies were unable to determine a relation between inspection programs and crash rates. Conclusively, there is an absence of research on the effectiveness of vehicle safety inspections on crash reduction. This study provides a short overview on this topic with inclusion of research directions and future scopes.

Publisher: Elsevier. Year: 2020.

 

Jalayer, M, Zhou, H., and S. Das. Exploratory Analysis of Run-Off-Road Crash Patterns. Data Analytics for Smart Cities. CRC Press, Boca Raton, FL.

The MCA method identifies patterns in complex datasets and measures significant contributing factors and their degree of association. To employ this method, datasets from the United States Road Assessment Program (usRAP), a program of the American Automobile Association Foundation for Traffic Safety, were obtained and 5 years (2009–2013) of ROR crash data in Illinois were gathered.

Publisher: CRC Press. Year: 2018.

 

Peer Reviewed Conference Articles (Computer Science)

  1. 2012. He, Y., X. Sun, L. Du, R. Jinmei, and S. Das. Level of service for parking facilities. 15th International IEEE Conference on Intelligent Transportation Systems, Anchorage, AK.   IEEE ITS12
  2. 2020. Wang, R.*, S. Das, and A. Mudgal. Patterns of Origin Destination Distributions: Rules Mining using Massive GPS Trajectory Data. Proceeding in the First International Conference on Urban Data Science, January 20-21, Madras, India.   UDS20
  3. 2021. Zubaidi, H., Obaid, I., Mohammed, H., Das, S., Al-Bdairi, NSS. Hot spot analysis of the crash locations at the roundabouts through the application of GIS. Journal of Physics: Conference Series, vol. 1895(1).   TRBAM15
  4. 2021. Das, S., Zubaidi, H. Autonomous Vehicles and Pedestrians: A Case Study of Human Computer Interaction. International Conference on Human-Computer Interaction.   HCI21

Peer Reviewed Conference Articles (Transportation Engineering)

Many of the presentation only papers were later published in different journals. I have not included those in the following. The following papers were only for presentations (not published in any journal) and these papers are all peer-reviewed.

  1. 2014. Das, S. Analyzing At-fault Crash-Prone Drivers of Louisiana associated with Multiple Crashes. SASHTO 2014 Annual Conference, New Orleans, LA, Aug 23-27 (2014 SASHTO Outstanding Graduate Research Award).   SASHTO14
  2. 2015. Das, S and X. Sun. Determining the Knowledge Gap in Performance Based Analysis of Geometric Design and Condition Incorporating Safety. The 94th Transportation Research Board Annual Meeting, Washington D.C., Jan 10-14.   TRBAM15
  3. 2015. Das, S and X. Sun. Zero-Inflated Models for Different Severity Types in Rural Two-Lane Crashes. The 94th Transportation Research Board Annual Meeting, Washington D.C., Jan 10-14.   TRBAM15
  4. 2016. Das, S Effectiveness of Inexpensive Crash Countermeasures to Improve Traffic Safety. The 95th Transportation Research Board Annual Meeting, Washington D.C., Jan 10-14.   TRBAM16
  5. 2016. Das, S., and X. Sun. Estimating Traffic Volume of Non-state Roadways with Support Vector Regression. The 95th Transportation Research Board Annual Meeting, Washington D.C., Jan 10-14.   TRBAM16
  6. 2016. X. Sun, S. Das, and N. Broussard. Developing crash models with supporting vector machine for urban transportation planning. The 17th Road Safety on Five Continents (RS5C) Conference, Rio de Janeiro, Brazil, May 17-19.   RS5C16
  7. 2017. Avelar, R., T. Lindheimer, K. Dixon, J. Miles, and S. Das. Safety Evaluation of the Seasonality of Crashes with Tire Debris on Highways and Freeways. The 96th Transportation Research Board Annual Meeting, Washington D.C., Jan 8-12.   TRBAM17
  8. 2017. Das, S., K. Dixon, R. Avelar, and K. Fitzpatrick. Using Machine Learning Techniques to estimate non-motorized trips for rural roadways. The 96th Transportation Research Board Annual Meeting, Washington D.C., Jan 8-12.   TRBAM17
  9. 2017. Das, S., X. Sun, and K. Dixon. Converting Four lane roadways into Five lane roadways on Urban structure: Study on Safety Effectiveness. Urban Street Symposium 5, Raleigh, North Carolina, May 21-24 (2017 Urban Street Symposium Best Paper Award).   USS17
  10. 2017. Das, S. Exploring SHRP2 NDS for the perspective of Self-Driving Cars in Difficult Driving Condition. Autonomous Vehicle Symposium, San Francisco, CA, Jul 10-14.   AVS17
  11. 2018. L. Minjares-Kyle, Das, S., G. Medina, and R. Henk. Knowledge about Crash Risk Factors and Self-Reported Driving Behavior: Exploratory Analysis on Multi-State Teen Driver Survey. The 97th Transportation Research Board Annual Meeting, Washington D.C., Jan 7-11.   TRBAM18
  12. 2018. Das, S., and A. Dutta. Knowledge Extraction from Transportation Research Thesaurus. The 97th Transportation Research Board Annual Meeting, Washington D.C., Jan 7-11.   TRBAM18
  13. 2018. Das, S., Fitzpatrick, K., and C, M*. Vehicle Speeds in Presence of Bicyclists. Joint Western and Texas District Meeting, Keystone, CO, June 24-27.   JWTDM18
  14. 2018. Das, S., L. Minjares-Kyle, R. Avelar, and B. Bommanayakanahalli*. Improper Passing related Crashes: Identifying Patterns using Negative Binomial Precise Rules. The 7th International Symposium on Naturalistic Driving Research (NDRS 2018), Blacksburg, VA, Aug 28-30.   NDRS18
  15. 2019. Das, S., and A. Dutta. Data Curation using Deep Learning. The 98th Transportation Research Board Annual Meeting, Washington D.C., Jan 13-17.   TRBAM19
  16. 2019. Sun, M., X. Sun, D. Shan, D. Armstong, and S. Das. Louisiana Pedestrian Crash Analysis with Multinomial Logit Model and Bayesian Network. The 98th Transportation Research Board Annual Meeting, Washington D.C., Jan 13-17.   TRBAM19
  17. 2019. Jalayer, M., M. O’Conell, H. Zhou, P. Szary, and S. Das. Application of Unmanned Aerial Vehicle to Inspect and Inventory Interchange Assets to Mitigate Wrong-Way Entries. The 98th Transportation Research Board Annual Meeting, Washington D.C., Jan 13-17.   TRBAM19
  18. 2019. Sun, X., and S. Das. Estimating Annual Average Daily Traffic for Low-Volume Roadways. The 12th TRB International Conference on Low Volume Roads, being held September 15–18, Kalispell, Montana.   TRB19
  19. 2020. Sun, M., X. Sun, M. Rahman, M. Akter, and S. Das. Two-Way Stop-Controlled Intersection Analysis with Zero-inflated Models. The 99th Transportation Research Board Annual Meeting, Washington D.C., Jan 12-16.   TRBAM20
  20. 2020. Sun, M., X. Sun, M. Rahman, M. Akter, and S. Das. Safety Performance Functions for Rural Two-Way Stop-Controlled Intersections. The 99th Transportation Research Board Annual Meeting, Washington D.C., Jan 12-16.   TRBAM20
  21. 2020. Das, S., K. Jha*, and A. Dutta. Vision Zero Hashtags in Social Media: Understanding End-User Needs from Natural Language Processing. The 99th Transportation Research Board Annual Meeting, Washington D.C., Jan 12-16.   TRBAM20
  22. 2020. Das, S., X. Kong*, R. Wang*, and A. Mahmoudzadeh*. Pedestrian Collisions with Bicyclist: Emotion Mining using YouTube Data. The 99th Transportation Research Board Annual Meeting, Washington D.C., Jan 12-16.   TRBAM20
  23. 2020. Dutta, A., and S. Das. Framework of a Job Lexicon for Future Transportation Workforce. The 99th Transportation Research Board Annual Meeting, Washington D.C., Jan 12-16.   TRBAM20
  24. 2020. Das, S., and A. Dutta. Co-Author Networks in Transportation Research: Findings from TRID Data. The 99th Transportation Research Board Annual Meeting, Washington D.C., Jan 12-16.   TRBAM20
  25. 2020. Mahmoudzadeh, A., Z. Elgart, S. Arezoumand, T. Hansen, and S. Das. Designing Transit Agency Job Descriptions for Optimal Roles: An Analytical Text-Mining Approach. ASCE International Conference on Transportation and Development (virtual due to COVID-19). pp. 356-368.   ICTD20
  26. 2021. Hosseini, P., M. Jalayer, and S. Das. Identifying Wrong-Way Driving (WWD) Crashes in Police Reports Using Text Mining Techniques. The 100th Transportation Research Board Annual Meeting (virtual due to COVID-19).   TRBAM21
  27. 2021. Hosseini, P., M. Jalayer, and S. Das. A Multiple Correspondence Approach to Identify Contributing Factors Related to Work Zone Crashes. The 100th Transportation Research Board Annual Meeting (virtual due to COVID-19).   TRBAM21
  28. 2021. Sun, M., X. Sun, M. Rahman, and S. Das. Calibration and Development of Safety Performance Functions for Rural Two-Lane Two-Way Stop-Controlled Intersections in Louisiana. The 100th Transportation Research Board Annual Meeting (virtual due to COVID-19).   TRBAM21
  29. 2021. Rahman, M., K. Dey, S. Das, and M. Sherfinski. Sharing the Road with Autonomous Vehicles: A Qualitative Analysis of the Perceptions of Pedestrians and Bicyclists. The 100th Transportation Research Board Annual Meeting (virtual due to COVID-19).   TRBAM21
  30. 2021.Kong, X.*, S. Das, H. Zhou, and Y. Zhang. Patterns of near-crash events in naturalistic driving dataset: applying rules mining. The 100th Transportation Research Board Annual Meeting (virtual due to COVID-19).   TRBAM21
  31. 2021. Das, S., and M. Theel*. Pandemic and Transportation Research: Bibliometric Analysis and Topic Modeling. The 100th Transportation Research Board Annual Meeting (virtual due to COVID-19).   TRBAM21
  32. 2021. Das, S., and R. Wang*. Racism discussed in Transportation Research: Bibliometric Analysis and Topic Modeling. The 100th Transportation Research Board Annual Meeting (virtual due to COVID-19).   TRBAM21
  33. 2021. Das, S. Traffic Fatalities by American Generations: Exploratory Evaluation using Person Level Data. The 100th Transportation Research Board Annual Meeting (virtual due to COVID-19).   TRBAM21
  34. 2022. Das, S., R. Tamakloe, H. Zubaidi, and V. Vierkant*. Virtual Public Engagement and Communications in a Transportation Conference during COVID-19. The 101st Transportation Research Board Annual Meeting, Washington D.C., Jan 9-13.   TRBAM22
  35. 2022. Das, S., M. Tabesh*, B. Dadashova, and C. Dobrovolny. Understanding Patterns of Contributing Factors in Encroachment-Related Work Zone Crashes. The 101st Transportation Research Board Annual Meeting, Washington D.C., Jan 9-13.   TRBAM22
  36. 2022. Das, S., Z. Wei*, and A. Dutta. Rules Mining and Narrative Analysis of Consumer Complaints on Hybrid Electric Vehicles. The 101st Transportation Research Board Annual Meeting, Washington D.C., Jan 9-13.   TRBAM22
  37. 2022. Das, S., and N. Trisha*. Understanding social media usage patterns by transit agencies. The 101st Transportation Research Board Annual Meeting, Washington D.C., Jan 9-13.   TRBAM22